Harnessing artificial intelligence to reduce phototoxicity in live imaging.

Artificial intelligence Data-driven microscopy Deep learning Fluorescence microscopy Live-cell super-resolution microscopy Live-microscopy Photodamage Phototoxicity

Journal

Journal of cell science
ISSN: 1477-9137
Titre abrégé: J Cell Sci
Pays: England
ID NLM: 0052457

Informations de publication

Date de publication:
01 Feb 2024
Historique:
medline: 7 2 2024
pubmed: 7 2 2024
entrez: 7 2 2024
Statut: ppublish

Résumé

Fluorescence microscopy is essential for studying living cells, tissues and organisms. However, the fluorescent light that switches on fluorescent molecules also harms the samples, jeopardizing the validity of results - particularly in techniques such as super-resolution microscopy, which demands extended illumination. Artificial intelligence (AI)-enabled software capable of denoising, image restoration, temporal interpolation or cross-modal style transfer has great potential to rescue live imaging data and limit photodamage. Yet we believe the focus should be on maintaining light-induced damage at levels that preserve natural cell behaviour. In this Opinion piece, we argue that a shift in role for AIs is needed - AI should be used to extract rich insights from gentle imaging rather than recover compromised data from harsh illumination. Although AI can enhance imaging, our ultimate goal should be to uncover biological truths, not just retrieve data. It is essential to prioritize minimizing photodamage over merely pushing technical limits. Our approach is aimed towards gentle acquisition and observation of undisturbed living systems, aligning with the essence of live-cell fluorescence microscopy.

Identifiants

pubmed: 38324353
pii: 342983
doi: 10.1242/jcs.261545
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : European Research Council
Pays : International

Informations de copyright

© 2024. Published by The Company of Biologists Ltd.

Déclaration de conflit d'intérêts

Competing interests The authors declare no competing or financial interests.

Auteurs

Estibaliz Gómez-de-Mariscal (E)

Instituto Gulbenkian de Ciência, Oeiras 2780-156, Portugal.

Mario Del Rosario (M)

Instituto Gulbenkian de Ciência, Oeiras 2780-156, Portugal.

Joanna W Pylvänäinen (JW)

Faculty of Science and Engineering, Cell Biology, Åbo Akademi University, Turku 20500, Finland.

Guillaume Jacquemet (G)

Faculty of Science and Engineering, Cell Biology, Åbo Akademi University, Turku 20500, Finland.
Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku 20520, Finland.
Turku Bioimaging, University of Turku and Åbo Akademi University, Turku 20520, Finland.
InFLAMES Research Flagship Center, Åbo Akademi University, Turku 20100, Finland.

Ricardo Henriques (R)

Instituto Gulbenkian de Ciência, Oeiras 2780-156, Portugal.
UCL Laboratory for Molecular Cell Biology, University College London, London WC1E 6BT, UK.

Classifications MeSH